A comparison of approaches to exploit budget allocation data in cross-sectional maximum likelihood estimation of multi-attribute choice models

Óscar González-Benito and Libia Santos-Requejo

Omega, 2002, vol. 30, issue 5, 315-324

Abstract: In this paper, four calibration approaches to exploit budget allocation data in maximum likelihood estimation of multi-attribute choice models are proposed. They differ on the implicit meaning of the dependent variable: (A) share of consumers according to the preferred alternative; (B) share of sales; (C) average share of consumer's budget; and (D) share of sales according to the preferred alternative. Differences between them can be conceived as depending on two circumstances: customer loyalty and customer selectivity. These are tested in the context of spatial consumer behavior, market response to hypermarket chains being represented as a function of their location strategies. Results show that different nuances on the definition of the dependent variable lead to slightly different relationships with the explanatory variables and to different predictive capabilities.

Keywords: Marketing; management; Multi-attribute; choice; models; Maximum; likelihood; estimation; Budget; allocation; data; Store; choice (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (2)

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